Every data center uses servers to provide computing resources (e.g., processing, memory space, network and disk I/O, etc.) that workloads need to function. As workloads proliferate and computing demands increase, server resources need to be expanded, or “scaled” to meet the increasing demands. There are two ways to scale server resources in a data center. The first is to add more servers or “scale-out.” For example, assume an enterprise has a virtual server running five applications and using 80% of the physical server's computing capacity. If the enterprise needs to deploy more workloads and the physical server lacks sufficient computing capacity to support the additional workloads, the enterprise may need to deploy an additional server to support the new workloads. Scale-out architecture also refers to clustered or disturbed computing approaches in which multiple small servers share the computing load for a single application. For example, a mission-critical workload may be deployed on two or more servers, with the processing being shard across those servers such that if one server fails, the other can take over and maintain the application's availability. The cluster can be scaled out with additional server nodes if more redundancy is needed.
Advances in technology, as well as server computing power, have increased the amount of resources that may be provided by a single server. Today's servers have far more processing, memory, and I/O capability than previous models within a similarly sized chassis. This approach is referred to as “scale-up” because the physical server can handle more and/or larger workloads. Referring again to the example set forth above, using a scale-up approach, it is possible to deploy a new server in the next technology refresh cycle with far more computing resources, migrate all of the workloads from the old server to the new one, take the old server out of service or allocate it to other tasks and be left with significantly more available resources to tackle additional production workloads without adding significantly to data center space or energy requirements.